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strategy-daily-briefing

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Updated 10-16 08:44

About this skill

Securities strategy analyst strategy daily report generation skill

Overview

This skill aims to simulate the daily review workflow of a professional securities strategist, through systematic organization ofthe day'smarket indices, style factors, industry sectors, capital flows, and micro-sentiment data, to generate a rigorously structured and logically clearStrategy Daily Briefing。

The core of the strategy daily report is not merely the listing of data, but rather the **"decoding of capital behavior"and"confirmation of the trading mainline"**. The report style is close to buy-side/sell-side strategy teams, focusing on discerning market turning points from micro-structure, and providing a clear trading plan for the next trading day.

Data Acquisition Strategy

Core data source: gildata-aidata

All market data, capital flow, and market sentiment data are preferentially obtained through the gildata-aidata service.

Data Requirements Recommended Tools Description
Index Quotes IndexRangeQuotation Obtain the price changes and turnover of the Shanghai Composite, Shenzhen Component, ChiNext, STAR 50, CSI 300, CSI 500/1000, Dividend Index, Moutai Index, etc.
Industry Quotes IndustryRangeQuotation or IndexRangeQuotation Obtain the price changes of the SW Level-1 industry indices, used to identify leading/lagging sectors.
Northbound/Stock Connect Capital HSGTTradeStats Obtain Shanghai-Hong Kong Stock Connect market trading statistics (net inflow/outflow, top ten active stocks).
Main Capital Flow StockMarketCapitalFlow Obtain net inflow/outflow of main capital for individual stocks/industries, and extra-large order/large order data.
Margin Trading and Securities Lending MarginTradingShortSelling (if available) Obtain changes in margin financing balance and securities lending balance.
ETF Subscription and Redemption ETFDailyInfo (if available) Obtain changes in shares of major broad-based/industry ETFs to judge institutional movements.
Macro/Policy Public Opinion MacroNewslist, PolicyMeetingsList Obtain major macro news, policy meetings, and official speeches of the day to assist in interpreting market logic.

Data Acquisition Priority

  1. Core Quotes and Capital: Prioritize gildata-aidata of IndexRangeQuotation、HSGTTradeStats、StockMarketCapitalFlow。
  2. Sentiment and Micro-structure: Prioritize obtaining the number of advancing/declining stocks and limit-up/limit-down data (if available) through gildata-aidata , or calculate through market data.
  3. Logical Interpretation Assistance: Combine MacroNewslist and policy meeting data to explain the reasons for sector anomalies.
  4. Supplementary Information：web_search is only used to supplement breaking news details, specific seat analysis of the Dragon and Tiger List, or hot money movements.

Execution Process

Phase One: Data Collection and Cleaning

  1. Market and Broad-Based Index Data

    • Tools：gildata-aidata IndexRangeQuotation
    • Query Examples： 
      调用 gildata-aidata IndexRangeQuotation
query: "上证指数 深证成指 创业板指 科创50 沪深300 中证500 中证1000 北证50"
time_range: "当日"
    • Core Indices: Shanghai Composite, Shenzhen Component, ChiNext, STAR 50, Beijing Stock Exchange 50, CSI 300, CSI 500/1000, Hang Seng Index.
    • Key Indicators: Price change, turnover (and its period-over-period change), and amplitude.

  2. Style factors and large-cap/small-cap performance

    • Style comparison: large-cap value (CSI 300) vs. small-cap growth (micro-cap stocks/CSI 2000).
    • Special indices: relative strength of the Dividend Index, Mao Index, and Ning Composite.

  3. Industry and thematic sector tracking

    • Tools：gildata-aidata IndustryRangeQuotation (or IndexRangeQuotation query industry indices)
    • Ranking of price changes in SW Level 1 industries (top 5/bottom 5).
    • Limit-up distribution: number of limit-up stocks, number of limit-down stocks, consecutive limit-up height (highest board), and limit-up failure rate.
    • Hot concepts: the strongest concept of the day (such as "low-altitude economy," "computing power," etc.) and its driving logic (policy/performance/events).

  4. Capital flows and liquidity

    • Foreign capital：gildata-aidata HSGTTradeStats(net inflow/outflow of northbound funds, main industries bought/sold).
    • Leveraged funds: daily changes in margin financing balance, amounts bought/repaid by margin traders.
    • Major institutions：gildata-aidata StockMarketCapitalFlow(industries with net inflows of main funds, changes in ETF shares).

  5. Sentiment and microstructure indicators

    • Money-making effect: ratio of advancing stocks to declining stocks, ratio of limit-up to limit-down stocks.
    • Options/futures: changes in premium/discount of SSE 50/CSI 300 stock index futures, implied volatility (IV) of options.
    • Turnover distribution: whether total market turnover breaks above/below key thresholds (such as 1 trillion, 1.5 trillion).

Phase 2: Logic analysis and inference

  1. Price-volume relationship and trend assessment

    • Analyze the "price-volume coordination" situation: rising with increased volume (healthy)/rising with decreased volume (divergence)/falling with increased volume (panic)/falling with decreased volume (reluctance to sell).
    • Determine whether the current market is in: trend continuation, range-bound washout, or a turning point.

  2. Trading mainline and capital game

    • Mainline confirmation: identify the direction with the strongest market consensus (such as "commodity price increases," "overseas expansion logic," "dividend defense").
    • Style rotation: whether there are signs of "high-low switching" (switching from high-position stocks to low-position stocks) or "large-small switching."
    • Institutions and hot money: performance differences between institutional stocks (trend) and hot money stocks (consecutive limit-up), determining whether the current market is dominated by institutions or hot money.

Phase 3: Report generation

  1. Generate a Markdown-format report

Use the following standard template to generate the final report:

# 策略日报 | [YYYY-MM-DD] [一句话核心观点]

> **分析师**：AI 策略研究团队  
> **报告日期**：YYYY-MM-DD  
> **市场情绪**：🟢 贪婪 (赚钱效应强) / 🟡 平衡 / 🔴 恐慌 (亏钱效应强)  
> **核心逻辑**：[简述当日市场核心交易逻辑。例如：“市场缩量震荡，资金从高切低，红利资产逆势走强，微盘股流动性危机暂缓，但连板高度受压……"]

---

## 一、 核心观点与交易计划

**1.1 盘面特征总结**
（总结当日大盘走势、成交量变化及核心特征。例如：“指数全天震荡走低，尾盘放量跳水，成交额萎缩至 1.2 万亿，市场呈现明显的防御特征。”）

**1.2 策略建议与明日计划**
*   **仓位建议**：[高/中/低] 仓位。
*   **配置方向**：
    *   **进攻**：[方向及逻辑，如“关注超跌的科技成长反弹”]
    *   **防守**：[方向及逻辑，如“逢低吸纳高股息红利资产”]
*   **操作节奏**：[如“轻仓试错，不见兔子不撒鹰”或“积极做多，回踩即买点”]

---

## 二、 大盘与风格复盘

| 指数 | 收盘价 | 涨跌幅 | 成交额 (亿) | 环比 | 简评 |
|------|--------|--------|-------------|------|------|
| 上证指数 | | | | | |
| 深证成指 | | | | | |
| 创业板指 | | | | | |
| 科创50 | | | | | |
| 微盘股指数 | | | | | |
| 恒生指数 | | | | | |

**风格与因子分析**：
*   **大小盘对比**：大盘价值与小盘成长谁占优？（如：“大盘蓝筹抗跌，微盘股普跌”）
*   **成长/价值剪刀差**：成长风格是否跑赢价值？
*   **量价结构**：分析当前量能水平对市场后续走势的支撑或压制作用。

---

## 三、 行业与主题追踪

**3.1 行业涨跌榜**
*   🔥 **领涨行业**：[行业1] (+%)、[行业2] (+%)、[行业3] (+%)
    *   **驱动逻辑**：[如“政策利好/涨价/业绩超预期”]
*   📉 **领跌行业**：[行业1] (-%)、[行业2] (-%)、[行业3] (-%)
    *   **驱动逻辑**：[如“获利盘兑现/利空消息/资金流出”]

**3.2 涨停梯队与连板分析 (游资视角)**
*   **涨停家数**：[数值] 家（不含 ST）
*   **跌停家数**：[数值] 家
*   **炸板率**：[数值]%
*   **连板高度**：[高度] 板 ([龙头股名称])
*   **梯队结构**：
    *   5板以上：[名称]
    *   3-4板：[名称]
    *   首板挖掘：[主要挖掘方向]

---

## 四、 资金面与流动性

| 资金类型 | 今日流向 | 累计流向 (近5日) | 资金态度 |
|---------|----------|-----------------|----------|
| 北向/陆股通 | | | |
| 融资余额 | | | |
| 主力资金 | | | |
| ETF申赎 | | | |

**资金博弈解析**：
*   **外资动向**：外资是在“抄底”还是“撤退”？主要流向哪些核心资产？
*   **杠杆资金**：融资客情绪如何？是否在加仓热门题材？
*   **机构调仓**：通过 ETF 份额变化和主力资金流向，推测机构是加仓宽基还是减仓行业？

---

## 五、 市场情绪与微观结构

*   **赚钱效应指标**：上涨家数 / 下跌家数 = [比值]
*   **涨跌停分布**：涨停 [数值] / 跌停 [数值]，市场赚钱效应 [极强/较弱/冰点]。
*   **期指升贴水**：IF/IC/IM 主力合约 [升水/贴水] [数值] 点，显示机构对后市预期 [偏多/偏空]。
*   **期权情绪**：PCR (Put/Call Ratio) 指标处于 [高位/低位]，暗示市场情绪 [过度悲观/过度乐观]。

---

## 六、 明日推演与关键点位

*   **明日推演**：基于今日量价与情绪，预判明日走势（如：“预计明日早盘惯性下探，随后在 3050 点附近获得支撑，全天呈现探底回升走势”）。
*   **关键支撑/压力**：
    *   强支撑：[点位]
    *   强压力：[点位]

---

## 七、 风险提示

*   [风险点 1]：如“量能持续萎缩导致流动性枯竭”
*   [风险点 2]：如“海外地缘冲突升级引发避险情绪”
*   [风险点 3]：如“高位连板股监管趋严，打击投机情绪”

---

*免责声明：本报告由 AI 自动生成，基于公开数据与量化模型分析，仅供参考，不构成任何投资建议。*

Notes

  • gildata-aidata first: all market, capital, and industry data queries should preferentially use the gildata-aidata service (such as IndexRangeQuotation, HSGTTradeStats, StockMarketCapitalFlow , etc.).
  • Data accuracy: ensure that cited core data such as index price changes and turnover are consistent with the day's closing data (usually based on data after 15:00).
  • Depth of logic: avoid merely being a data porter; you must explain "why it rose/fell," especially the logic behind capital flows (such as "good news priced in," "high-low switching").
  • Microstructure: Attach great importance to micro indicators such as consecutive limit-up height and limit-up failure rate; these are the core basis for judging short-term sentiment (hot money/retail sentiment).
  • Professional Terminology: Proficiently use strategic analysis terms such as "volume-price divergence," "high-low switch," "shrinking-volume slow decline," "volume breakout," "sentiment freezing point," and "profit-loss ratio."
  • Objective and Neutral: When analyzing capital flows, note the limitations of the "main net inflow" algorithm and combine multi-source data for cross-validation.

Example Invocation

User input: "Generate today's strategy daily report"

Skill execution:

  1. Obtain market indices: gildata-aidata IndexRangeQuotation (query SSE, SZSE, ChiNext, STAR 50, etc.)
  2. Obtain industry gains and losses: gildata-aidata IndustryRangeQuotation (or query industry indices)
  3. Obtain capital flows: gildata-aidata HSGTTradeStats + StockMarketCapitalFlow
  4. Obtain macro public opinion: gildata-aidata MacroNewslist
  5. Analyze volume-price and sentiment: combine data to calculate the advance-decline ratio, month-over-month turnover, etc.
  6. Write the report: generate a Markdown-format strategy daily report according to the template
  7. Output the report: display the complete report content directly in the conversation

Skill Update Log

2026-05-11 Update：

  • Core Data Source Change: Fully integrated with gildata-aidata service.
  • Clear Tool Mapping: Added a tool comparison table, covering index quotes (IndexRangeQuotation), northbound capital (HSGTTradeStats), main capital (StockMarketCapitalFlow), etc.
  • Process Optimization: Clarified the execution order of first obtaining Gildata data, then combining capital fundamentals and sentiment for logical deduction.